Turning data into information

There was an interesting discussion on NPR recently about the words that teams use to define themselves.  One example that was used was "IT" for Information Technology.  The person speaking said that this defined the mechanics of the group, but not its purpose.  He said that the teams currently known as IT should be known as IA, for information access, since that is their purpose.

I found that really interesting, since I am old enough to remember when internal technology teams were called DP - for data processing.  In those days there was limited access to the mainframe and you had this sense of a massive computer in a refrigerated room cranking through large amounts of data and spitting out a report.  Other than the size of the computer, I don't think much has changed - in fact there is probably more manual and spreadsheet analysis of data done today than ever before.  Most technology organizations are still in data processing - they shape and clean the data and provide it in a context that most of us can then analyze using Excel.

If you think about it, there is a disturbing trend - the more computers and the more computing power we have, the more data we generate, and the more demand there is for analysis of the data.  It would seem that the analysis should become much more automated, that humans should be able to dictate certain factors or trends and have the systems notify the humans when those things occur.  Clearly some of that exists, but not nearly enough - there is simply too much computing power given over to maintaining, storing and cleaning data, and not nearly enough to presenting information that people can make decisions about.

At what point do we recognize our plight and get angry, like a shipwrecked sailor dying of thirst in the ocean?  In any business, we have tons of data.  Data storage firms are doing a killer business selling hardware and software to store all of this data.  Yet we still employ too many people massaging data and evaluating it and analyzing it, which takes too much time and effort away from making and acting on important decisions.

It's time to stop asking what data we need and start asking what decisions we are trying to make.  It's time for software companies to help us turn data into actionable information.  It's time to free people from Excel and have them work on enacting what they've learned, rather than reading the tea leaves of disparate data.  When do senior managers of business functions stand up and say "I'm mad as hell, and I'm not going to take this anymore"?

Just once I'd like to talk to someone who does not ask if the data can be exported into an Excel spreadsheet.

Comments

[John]

When "business intelligence" running against multidimensional cubes works (Cognos, Business Object, even Oracle Discoverer), it's what you're talking about: presenting the data in a way that is READY FOR ANALYSIS.

Plus, having everyone use a shared tool that builds the data from a common repository/datamart also produces the effect know as "one version of the truth." Everyone is using the same tool, with the same metrics -- no rogue Excel spreadsheets where individual managers have cooked their data.

[Jeffrey Phillips]

John:

Thanks for your comments and I agree. One common version of the truth used consistently across the business for making decisions is what I want.

However, I worry about layering more and more systems - BI or reporting - on top of the transactional systems which generated the original data. Having worked with a BI vendor, I know how a BI system can have intended or unintended bias in the computation of the data. What we really need is for our day to day systems to present us with actionable information, not to simply park data.